UrbanFootprint and the new shape of scenario planning tools

Though the concept of scenario planning has been in use for some two decades in the field of urban and regional planning, it is now becoming part of the professionally-accepted mainstream of the planning profession. With the passage of laws such as SB 375 in California, SB 1059 (as well as other related legislation) in Oregon, and similar legislation in other states, regions must now consider how to reduce greenhouse gas (GHG) emissions by planning for land use development patterns that will lessen the need for automobile travel, among other GHG-reduction strategies. Scenario planning tools allow regions to compare different urban growth alternatives, to evaluate their performance for a range of metrics, including but not limited to GHG emissions.

UrbanFootprint Scenario Ecosystem

So, what sorts of advancements have been made in the development of UrbanFootprint to differentiate it from previous-generation scenario planning tools?

Fully open-source software stack.

UrbanFootprint v1.1 Software Stack

UrbanFootprint is a powerful scenario land use planning, modeling and data organization framework designed to facilitate more informed planning by practitioners, public agencies, and other stakeholders. Its development is led by Calthorpe Associates, a planning and urban design firm with over two decades of experience with regional and urban scenario planning. Built on fully open-source software platforms and tools, UrbanFootprint requires no proprietary software of any kind. It runs on the Ubuntu Linux 64-bit operating system; Postgresql drives the database back-end; this allows for PostGIS to provide GIS functionality; and for Postman to provide multi-user simultaneous editing capabilities. Queries and model logic use a combination of PGSQL and Python; Django, Apache, and Spoutcore interact with Redis Queue and Celery to allow for a web-driven, platform-agnostic user interface that is able to schedule complex server-side tasks and report the results back seamlessly. The map interface is service by Polymaps and Mapnik, interacting with Tilestache; charting is provided by d3. There are essentially no limitations to the amount of hardware that can be deployed on behalf of UrbanFootprint, from a desktop virtual-machine environment to the largest super-computing arrays. This flexibility allows it to be scalable, from analysis of a single development to an entire state, and beyond.

Automated base data loading process.

Experienced planners know that more than 70% of the time spent on any project is consumed by finding, assembling, processing and cleaning the input data required before the meat of the analysis can occur. UrbanFootprint leverages the experience of the Calthorpe Associates team to automate as much of this process as possible, so that the base data preparation process can be compressed from months or years to days or weeks. A series of scripts are used to normalize data of varying quality, type, and scale from a wide range of sources, and import them into the model analysis framework.

Base Data Development Process

Future growth scenarios in UrbanFootprint are built upon a base-year canvas that provides a baseline assessment of: existing land use; demographic characteristics, including Census population, housing and jobs characteristics; land cover; environmental features; parcel-baed data on housing, employment and population; control total data from MPOs or other agencies, generally at the traffic analysis zone (TAZ) resolution; roadway and transit data; and other conditions.

Full set of calibrated starter place & building types.

UrbanFootprint includes a library of more than 35 Place Types and 50 building types that make up the palette of development options used to translate or “paint” scenarios. Place Types – each composed of a mix of Building Types (based on studies of over 300 real-world buildings) – are the land use building blocks of future scenarios, and represent the complete range of potential development types and patterns that make up a scenario. They include a range of mixed-use centers, residential areas of varying densities and types, employment and industrial areas, and other land use types that make up existing and future urban land uses.

Components of Place Types

Study Areas

UrbanFootprint’s Place Types are calibrated based on studies of at least three exemplary places per type, generally drawn from across California and the US; the Building Types are based on detailed studies of a complete range of building types found in the Western United States and beyond. The UrbanFootprint Place Type library can be utilized by cities, regions, or MPOs as they develop their own plans – either as an “off the shelf” library or customized for their specific needs.

Automated existing plan translation engine.

UrbanFootprint includes tools that quickly translate any existing plan or scenario into the model’s common language of Place and Building types, based on only five vectors: Gross dwelling unit density; gross employment density; walkable street intersections per square mile; the percentage of employment that is retail; and the percentage of employment that is office + industrial. The model can translate jurisdictional, county, regional, and other plans, no matter what tool or process was used to create them. Once an existing plan is translated into UrbanFootprint, additional editing or scenario painting can be performed, and analytical engines can be run. The translation tools also provide the capacity to maintain a common “quilt” of local land use and transport plans, and perform consistent, compatible analysis on individual plans or combinations thereof.

UrbanFootprint Scenario Translation Process

At the state and regional levels, UrbanFootprint can be used to integrate or stitch together Sustainable Community Strategies (SCSs), Regional Transportation Plans (RTPs) or similar regional scenarios, and general/local-scale plans as they are produced. This comprehensive plans database can be made available to local governments looking to coordinate their land-use assumptions with other localities and regions for SCS/regional planning and analysis.

Web-based scenario painting and editing tool.

UrbanFootprint Painting Tool

UrbanFootprint’s web-based painting tool is integrated into the model’s graphical user interface. It allows the user to edit or build upon a translated plan or scenario, or create new scenarios from scratch. Though the initial version of UrbanFootprint was built to operate using the 5.5-acre (150-meter) grid cell as its basic unit of analysis, it has since been updated to become geography-agnostic; the user can now paint on any level of geography, whether it be parcel, pseudo-parcel, grid cell, zone or any other topologically-clean geography type. The web-based scenario painter can display and link to regularly updated base maps and data (e.g. Google Maps, Mapquest, Bing, OpenStreetMaps, etc.); user-controlled scenario, base or reference data is displayed on top of this cloud-based basemap data. This division of labor allows the scenario painter’s tools to enable quick painting and editing of the place types or building types used to describe the form of growth, and dynamic viewing of scenario results iteratively in order to inform the scenario creation process in realtime.

Integrated, calibrated analysis engines.

UrbanFootprint comprises a suite of tools and analytical engines that decrease the time and resources required for land use scenario development, while significantly increasing the technical capacity of state, regional, and local users to analyze the fiscal, environmental, transportation, and public health impacts of plans and policies. Moreover, it provides a common data framework within which planning efforts at various scales can be integrated and synced.

UrbanFootprint Analysis Engines

The model currently includes analytical engines that produce results for the following metrics (with more to come as the model is advanced through deployment and research-based activities):

Land consumption

Vehicle miles traveled (VMT), travel mode, and fuel consumption

Transportation greenhouse gas (GHG) and air pollutant emissions

Building energy and water consumption, costs, and related GHG emissions

Household costs for housing, transportation and utilities

Public health impacts and costs (physical activity/weight-related, pollutant/respiratory-related, and pedestrian-safety)

Local fiscal impacts (capital infrastructure and operations and maintenance costs, and tax/fee revenues)

Did I mention open-source?

Open source isn’t just about the software stack; it’s about the philosophy of spreading the benefits of further tool development equally back to members of the user community, without the need to charge ongoing licensing fees. When one user, such as a Metropolitan Planning Organization (MPO) develops a new methodology for tackling a problem and codes this solution up as a new script, forming the basis for a new UrbanFootprint module, this module will become available to all of the existing and future UrbanFootprint users without any additional fees; their only expenditure would be related to the staff (or consultant) time required to calibrate and deploy the new module within their region. For instance, let’s say MPO A develops a new module to calculate the fiscal impacts of rural land development; MPO C could then deploy this module within their own region, and only need to pay for the staff time required to calibrate their local data inputs to make the module work (local farm labor, land, and other agricultural input costs, in this case). Moreover, UrbanFootprint provides a framework within which the advancement can be automated and shared; business as usual in the planning profession tends to see many individual actors innovate and solve problems independently, without being able to easily take advantage of solutions that may already have been developed elsewhere by other agencies.

The bottom line.

UrbanFootprint represents the next generation of scenario planning tools; in going beyond mere sketch planning, it blurs the lines between scenario creation, scenario analysis, modeling, implementation, regional planning operations, research and public engagement. By making such powerful resources available to everyday planning practitioners, it represents the potential to enable better planning by default. The realization of this potential will be hastened through increasing projects and deployments that add to the base of contributing use and development partners.